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Ruscio, John; Kaczetow, Walter – Multivariate Behavioral Research, 2009
Interest in modeling the structure of latent variables is gaining momentum, and many simulation studies suggest that taxometric analysis can validly assess the relative fit of categorical and dimensional models. The generation and parallel analysis of categorical and dimensional comparison data sets reduces the subjectivity required to interpret…
Descriptors: Classification, Models, Comparative Analysis, Statistical Analysis
Peer reviewedHenschke, Claudia I.; And Others – Multivariate Behavioral Research, 1974
The technique presented accomodates multiple populations and a mixture of variable types. It is based on the linear discriminant function and the sequential concept. Also presented is an example in which the technique is used to obtain the classification rule to predict the career choices of individuals based upon a mixture of variable types.…
Descriptors: Classification, Measurement Techniques, Predictor Variables, Probability
Peer reviewedHuberty, Carl J.; Curry, Allen R. – Multivariate Behavioral Research, 1978
Classification is a procedure through which individuals are classified as being members of a particular group based on a variety of independent variables. Two methods of makin such classifications are discussed; the quadratic method is seen to be superior to the linear under certain constraints. (JKS)
Descriptors: Analysis of Covariance, Classification, Discriminant Analysis, Groups
Peer reviewedLevin, Joseph – Multivariate Behavioral Research, 1974
Descriptors: Classification, Correlation, Factor Analysis, Mathematical Models
Peer reviewedHuberty, Carl J.; Blommers, Paul J. – Multivariate Behavioral Research, 1974
Descriptors: Analysis of Covariance, Analysis of Variance, Classification, Discriminant Analysis

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